The primary goal of this research is to develop and validate an engineering control system paradigm for obtaining quantitative insight into how multiple interdependent hemostatic processes interact to control blood loss safely and effectively following vessel injury. A novel quantitative modular modeling and analysis technique for organizing the mechanistic details of this biological process will be developed and validated experimentally. The resulting mathematical model will be used to elucidate mechanisms of hemostatic disorders from a control system perspective, and to generate testable hypotheses about effective treatment. The specific question to be answered is: Quantitatively, how do the various components of the entire hemostatic process work together to produce fast, effective and stable responses to vascular injury under normal conditions?
The specific tasks that will be performed are:
Task 1: Model Development. Develop a detailed control system block diagram representation of the components of hemostasis, derive mathematical models for each component and integrate into a holistic, comprehensive dynamic model.
Task 2: Model Validation (Experimental). In a continuing collaboration the PIs will validate the predictions of each principal module of the overall model against independent experimental data.
Task 3: Model Analysis and Hypothesis Generation. Computation studies and theoretical analyses of the model will be carried out; derivation of quantitative insight into pathological disorders from a control system perspective; and generation of hypothesis regarding effective treatment regimens in terms of optimal compensation for component malfunction responsible for the identified disorder.
Intellectual Merit Systemic changes in life sciences research have created opportunities for mathematical modeling to play a major role in developing quantitative and predictive understanding of complex biological phenomena. With ever improving experimental capabilities facilitating the acquisition of more refined data on the most intricate cellular and molecular mechanisms, increasing computational power has steadily steered mathematical modeling in systems biology towards adopting ?bigger and more complex? representations of these complex systems. For the specific problem of hemostasis there are currently no holistic quantitative models of the complete hemostasis process perhaps because many of the constituent components are quite complex in their own right, and a ?standard? attempt at developing a holistic model is not likely to be very useful. By recognizing that at the heart of hemostasis is an automatic biological control system, this research aims to deploy concepts from engineering control systems to develop a comprehensive hemostatic process model that achieves fidelity without sacrificing analytical tractability. The PIs envision two kinds of primary impact for this research: (i) Technical: an improved quantitative understanding of how this biological process is regulated under normal circumstances, and how the characteristics of the whole emerge from the connection of the individual component parts, with implications for clinical practice in the form of more precise treatment of hemophilia and thrombophilia; (ii) Methodological: demonstrating how to achieve high-fidelity and analytical tractability simultaneously in models of extremely complex biological phenomena.
Broader Impact At the heart of the evolving undergraduate training program is the issue of how to integrate biology within the classical chemical engineering curriculum. This research addresses theoretically and with experimental validation, issues that are perfect for introducing students to biological control systems, and how to employ such simulation tools as SIMULINK for modeling and understanding such systems. The results of this research will be integrated into the teaching curricula and widely disseminated through publications and presentations to other educators and researchers. In addition, the PI, as a minority himself, is committed to recruiting under-represented groups into the chemical engineering discipline in general and systems biology research in particular, and should be able to attract minority students to participate in this effort.
